◆ Google Looker

Monitor Data Studio log events

This is real work, not a feature someone invented — it comes from real job ads and real questions people asked. Below are four ready AI prompts: get it done, make it easy for the next person to say yes to, work out the right move when you are stuck, and stop it coming back.

4prompts

The same task, four prompts

today's deadline · the next reviewer · the stuck moment · the pattern
AExecute — do the immediate taskMonitor log events for the 'Marketing Performance Dashboard' for any errors or failed data…+
Monitor log events for the 'Marketing Performance Dashboard' for any errors or failed data refreshes over the next 24 hours.
when the reply comes backPush once: ask it to sharpen the weakest part, and to say what it assumed. Helpful?
BImprove — make it easier to acceptBefore I set up monitoring for the new 'Executive Overview' dashboard, can you help me…+
Before I set up monitoring for the new 'Executive Overview' dashboard, can you help me configure alerts that distinguish between minor data latency and critical data source failures, so we don't get flooded with false alarms?
when the reply comes backPush once: ask it to sharpen the weakest part, and to say what it assumed. Helpful?
CDecide — diagnose the stuck momentI just received an alert that the 'Sales Pipeline' dashboard's data refresh failed, but the…+
I received an alert that the 'Sales Pipeline' dashboard's data refresh failed, but the dashboard itself still shows recent data.
I just received an alert that the 'Sales Pipeline' dashboard's data refresh failed, but the dashboard itself still shows recent data. Sarah in sales is asking if she can trust it for her quarterly review presentation this afternoon. I'm worried it's a partial failure or a caching issue, but I don't want to tell her it's fine if it's not. What's the best way to quickly verify the data's integrity and advise her?
when the reply comes backPush once: ask it to sharpen the weakest part, and to say what it assumed. Helpful?
DBecome — change the patternI'm constantly reacting to data quality issues reported by users, instead of proactively…+
I'm constantly reacting to data quality issues reported by users, instead of proactively catching them with log monitoring.
I'm constantly reacting to data quality issues reported by users, instead of proactively catching them with log monitoring. It feels like I'm always behind the curve, and user trust is eroding. What habit should I change to better leverage log events to identify potential data problems before they impact our stakeholders?
when the reply comes backPush once: ask it to sharpen the weakest part, and to say what it assumed. Helpful?

Questions people actually ask

honest answers, no sign-up

Every task here was seen in the real world. Someone doing the job named it, a real job ad asked for it, or a lot of people asked about it online.

If nothing real showed a task, it is not on the page. That is the whole rule.

They are the same job approached four ways, because what you need depends on where you are.

Get it done today. Make it easy for the next person to say yes to. Work out the right move when you are stuck. Learn the pattern so the job stops coming back.

For most of these jobs it can carry the heavy thinking - draft it, sort it, check it, rehearse it with you.

It cannot sit in your chair, take the blame when a number is wrong, or notice what nobody wrote down. Let it do the first 80%. Keep the last 20% that is truly yours.

No. Copy any prompt and paste it into the AI you already use. No account, no score, no wall in the way.

Any of them. The prompts describe the work rather than naming a product, so they are not tied to one assistant.

That is also why they keep working when you switch.

Change it freely. Every prompt is a starting line, not a rule.

Put in your real numbers, your real names and your real deadline. The more you make it yours, the better the answer comes back.

The tasks come from real job ads, published job data and the questions people ask in public forums.

The steps come from Google Looker's own documentation, with practitioner sources for the traps the manual does not mention.

Push once. Ask it to sharpen the weakest part and to say what it assumed.

Most wrong answers come from a missing detail rather than a bad prompt - tell it the thing it could not know.